no code implementations • 19 Oct 2012 • Juhi Ameta, Nisheeth Joshi, Iti Mathur
Gujarati is a resource poor language with almost no language processing tools being available.
1 code implementation • 24 May 2013 • Snigdha Paul, Nisheeth Joshi, Iti Mathur
We live in a translingual society, in order to communicate with people from different parts of the world we need to have an expertise in their respective languages.
no code implementations • 12 Jul 2013 • Juhi Ameta, Nisheeth Joshi, Iti Mathur
Machine Translation for Indian languages is an emerging research area.
no code implementations • 15 Jul 2013 • Deepti Bhalla, Nisheeth Joshi, Iti Mathur
Proper transliteration of name entities plays a very significant role in improving the quality of machine translation.
no code implementations • 15 Jul 2013 • Jyoti Singh, Nisheeth Joshi, Iti Mathur
In this paper we show the development of the tagger.
no code implementations • 23 Jul 2013 • Nisheeth Joshi, Hemant Darbari, Iti Mathur
In this article, we shall present the evaluation of some machine translators.
no code implementations • 4 Sep 2013 • Rashmi Gupta, Nisheeth Joshi, Iti Mathur
This paper considers the problem for estimating the quality of machine translation outputs which are independent of human intervention and are generally addressed using machine learning techniques. There are various measures through which a machine learns translations quality.
no code implementations • 2 Oct 2013 • Vaishali Gupta, Nisheeth Joshi, Iti Mathur
In stemming, we separate the suffix and prefix from the word.
no code implementations • 2 Oct 2013 • Jyoti Singh, Nisheeth Joshi, Iti Mathur
Part-of-speech (POS) tagging is a process of assigning the words in a text corresponding to a particular part of speech.
no code implementations • 2 Oct 2013 • Deepti Bhalla, Nisheeth Joshi, Iti Mathur
This paper presents a novel approach to machine translation by combining the state of art name entity translation scheme.
no code implementations • 2 Oct 2013 • Vaishali Gupta, Nisheeth Joshi, Iti Mathur
The work is based on the evaluation of English to Urdu Machine translation.
no code implementations • 15 Nov 2013 • Nisheeth Joshi, Iti Mathur, Hemant Darbari, Ajai Kumar
Machine translation evaluation is a very important activity in machine translation development.
no code implementations • 22 Nov 2013 • Pooja Gupta, Nisheeth Joshi, Iti Mathur
In this paper, we show an approach which can provide automatic ranks to MT outputs (translations) taken from different MT Engines and which is based on N-gram approximations.
no code implementations • 27 Dec 2013 • Rashmi Gupta, Nisheeth Joshi, Iti Mathur
There are various methods for estimating the quality of output sentences, but in this paper we focus on Na\"ive Bayes classifier to build model using features which are extracted from the input sentences.
no code implementations • 28 Mar 2014 • Iti Mathur, Nisheeth Joshi, Hemant Darbari, Ajai Kumar
Structures which can facilitate open world assumptions and can be flexible enough to incorporate and recognize more than one name for an entity.
no code implementations • 19 Apr 2014 • Iti Mathur, Nisheeth Joshi, Hemant Darbari, Ajai Kumar
Two different ontologies assimilating same knowledge tend to use different terms for the same concepts.
no code implementations • 10 Jul 2014 • Pooja Gupta, Nisheeth Joshi, Iti Mathur
Machine Translation is the challenging problem for Indian languages.
no code implementations • 12 Jul 2015 • Shruti Tyagi, Deepti Chopra, Iti Mathur, Nisheeth Joshi
Machine Translation is one of the research fields of Computational Linguistics.